招聘
必备技能
Machine Learning
Amazon Photos empowers customers to preserve, share, and relieve their memories across mobile applications, web, desktop, Amazon devices, and as part of Alexa+. We strive to provide customers with the best memories companion for them and their families.
We're looking for a Software Development Engineer that wants to build and scale foundational services that power our computer vision and artificial intelligence capabilities. In this role, you'll architect and develop solutions that process millions of photos daily, enabling intelligent features that bring customer memories to life. You'll work at the intersection of large-scale distributed systems and AI technologies, creating services that form the backbone of Amazon Photos' next-generation features.
- Key job responsibilities
- Design and implement scalable, fault-tolerant services that power computer vision and AI features across the Amazon Photos ecosystem
- Build and optimize full-stack solutions that handle massive amounts of photo and video data while maintaining high performance and reliability
- Architect and develop ML model serving infrastructure and pipelines for real-time computer vision applications
- Drive technical decisions and architecture discussions for critical infrastructure components
- Collaborate with ML scientists to productionize computer vision models and optimize their performance at scale
- Implement and maintain observability solutions for complex distributed systems
- Mentor junior engineers and contribute to building a culture of engineering excellence
- Partner with product managers and other teams to define technical roadmaps and deliver customer-facing features
About the team
We operate at massive scale, processing billions of customer photos while maintaining high availability and low latency. Our team leverages technologies in distributed systems, computer vision, and machine learning to create innovative solutions that delight customers. We're building the future of how people interact with their memories, using AI to create more personalized and meaningful experiences.
Basic Qualifications
- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language
Preferred Qualifications
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
- Experience with computer vision or machine learning technologies
- Experience building and maintaining large-scale distributed systems
- Knowledge of modern AI/ML frameworks and serving infrastructure
- Experience with cloud technologies and microservices architecture
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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关于Amazon

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
员工数
Seattle
总部位置
$1.5T
企业估值
评价
2.9
10条评价
工作生活平衡
2.8
薪酬
3.7
企业文化
2.5
职业发展
2.3
管理层
2.1
35%
推荐给朋友
优点
Good pay and compensation
Strong benefits package
Flexible scheduling options
缺点
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
薪资范围
4个数据点
L2
L3
L4
L5
L6
L2 · Data Analyst L2
0份报告
$108,330
年薪总额
基本工资
$43,332
股票
$54,165
奖金
$10,833
$75,831
$140,829
面试经验
10次面试
难度
3.7
/ 5
时长
21-35周
录用率
20%
体验
正面 10%
中性 10%
负面 80%
面试流程
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
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